FAS Student Papers

Recent advancements in multimodal Generative AI may democratize specialized architectural tasks like interpreting technical drawings and creating 3D CAD models which traditionally require expert knowledge. This paper presents a comparative evaluation study of two systems—GPT-4o and Claude 3.5—in the task of architectural 3D synthesis. It takes as a case study two buildings in Palladio’s Four Books of Architecture (1965): Villa Rotonda and Palazzo Porto. High-level architectural models and drawings of the buildings were prepared inspired by Palladio’s original text and drawing corpus. Through sequential text and image prompting, the study characterizes intrinsic abilities of the systems in (1) interpreting 2D/3D representations of buildings from drawings, (2) encoding the buildings into a CAD software script, and (3) self-improving based on outputs. While both systems successfully generate individual parts, they struggle to accurately assemble these parts into the desired spatial relationships, with Claude 3.5 showing overall better performance, especially in self-correcting its output. The study contributes to ongoing research on benchmarking the strengths and weaknesses of off-the-shelf AI systems in intelligent human tasks requiring discipline-specific knowledge. The results show the potential of language-enabled AI systems to act as collaborative technical assistants in the architectural design process.

Heterochronic parabiosis, a surgical process connecting the circulatory systems of young and old mice, is used to study the regulation of tissue aging and regeneration via protein factors found in blood. Several factors have been shown to improve central nervous system function and ameliorate the effects of aging in mice by increasing stem cell regeneration, but it is less well known which genes are differentially expressed in old mice to induce this “aging reversal” phenotype. We performed an in silico analysis of single cell RNAsequencing (scRNA-seq) data from parabiosed mice to identify transcription factors (TFs) whose expression is significantly dysregulated between old mice and old-young parabiosed mice, which represent the reversed aging state. We employed single-cell regulatory network inference and clustering (SCENIC), a computational framework which identified gene regulatory networks (GRNs) from scRNA-seq data. Regulatory networks from old, old-old parabiosed (as a control), and old-young parabiosed mice were identified from scRNA-seq gene expression matrices spanning 31 cell types. Network activity was then scored by SCENIC as a function of gene expression levels in the networks. These scores formed the basis of comparison of transcription factors between old mice and parabiosed mice. The TFs identified thus far were verified against a set of TFs thought to be dysregulated with parabiosis via differential gene expression analysis. Preliminary results indicated that GRN analysis provides a robust platform for identifying TFs whose expression is significantly altered with parabiosis, and completion of this study will yield a comprehensive understanding of these TFs. In the future, these TFs can serve as therapeutic targets, as compounds can be administered to modulate the expression of these TFs and the genes they regulate in old mice to match the expression profiles identified in old-young parabiosed mice, potentially achieving the aging reversal phenotype.

While the need for rigorous and affordable prostheses in developing countries is serious, little to none of these devices exist and are available to lower-limb amputees. In addition, pediatric amputees in low-income areas are further prohibited from accessing these technologies; the rapid growth rate of their limbs calls for frequent replacements of prostheses, making existing solutions economically unfeasible.

In this thesis, a model was generated to depict how the kinematic and kinetics of healthy pediatric gait vary with age. This model was then used to optimize the design of a passive ankle prosthesis, which uses a spring and damper system to store and release energy to the ankle joint. Most importantly, this system was designed to adapt to the changing gait pattern and dynamics of a pediatric amputee.

The presented paradigm—using a computer model to efficiently predict the gait produced by various prosthesis design—allows for the creation of affordable, accurate, and tailored devices for individuals who currently are forced to settle for one-size-fits all passive solutions. This approach promises to substantially increase the access to prostheses for children around the world.

90 Reasons is a list of prospective benefits cellular agriculture may offer upon global-scale introduction this century.

The use of affirmative action has been at the forefront of the debate regarding the fairness of the college admissions process for years. Utilizing data from the National Longitudinal Survey of Freshman (NLSF), M. Fischer and Massey (2007) test the effects of race-based admission policies. Providing a specific focus on cumulative GPA, they conclude that the effect of affirmative action is minimal. Testing the robustnessof this claim, I replicate their results. Their regression specification suffers from issues of high correlation between their SAT and individual affirmative action variable. When adjusting for these problems, affirmative action actually has a negative effect on cumulative GPA. There is a 0.10 reduction in GPA for every 100-point increase in the difference between an individual’s SAT score and the institutional average.

In their controversial work The Bell Curve, Charles Murray and Richard Herrnstein hypothesize that intelligence plays a significant role in determining later life outcomes. Using data from the 1979 National Longitudinal Survey of Youth, Herrnstein and Murray specifically claim that Youth IQ is more important than Parental Socioeconomic Status in affecting future odds of living in poverty. We explore their hypothesis using the same statistical decisions but on a new data set: the 1997 National Longitudinal Survey of Youth. Our findings mirror those of Herrnstein and Murray; IQ has a larger effect than socioeconomic status on the likelihood of being in poverty, though the overall effect of both is diminished. We find that increasing Youth IQ by one standard deviation is expected to decrease the odds of ending up in poverty by 35 percentage points, compared to the 13 percentage point decrease from similarly increasing Parental Socioeconomic Status.

The Bell Curve (Herrnstein and Murray (1994)) is a very controversial piece of economics literature. The Bell Curve, which examines the effect of IQ on various social problems, is broken down into four sections: “The Emergence of the Cognitive Elite”, “Cognitive Classes”, “Social Behaviors”, and “National Context.” For survey statistics, Herrnstein and Murray (1994) use the National Longitudinal Survey of Youth (NLSY) data from 1979, which includes 12,686 people from ages 14 to 22, and contains Socioeconomic status (SES), IQ, and other related data. Herrnstein and Murray (1994) generate IQ from the Armed Forces Qualification Test (AFQT), a test all entrants to the Army take as an intelligence or IQ test. The Bell Curve concludes that self-isolation of the “cognitive elite,” defined in terms of IQ, has led to class stratification. Herrnstein and Murray (1994) believe that IQ is the best and most robust measure that is correlated to many resulting social problems, including poverty. I replicate The Bell Curve results that relate SES and IQ to poverty. I then examine the robustness of their results by examining a variety of regression specifications. I find that IQ is more correlated with poverty than SES in every regression, regardless of what is included in the regression, by a factor of 3.

The Bell Curve by Charles Murray and Richard Herrnstein is one of the most controversial academic works of the last few decades. Using data from the National Longitudinal Survey of Youths (1979), we performed a number of regressions of poverty status in 1989 on parental socioeconomic status, IQ, race, sex, and age. We replicate their results which show that IQ is a more important predictor of poverty status than parental socioeconomic status (SES). We extend their analysis to other groupings and find that, while similar, the underlying relationship between the variables and poverty status varies across groups. We then compared ratios of the percentage of the top 25% to bottom 25% of either IQ or parental SES in poverty. We found that parental SES had three times the predictive power as SES for black respondents and twice the predictive power for Hispanic respondents over whites, also finding a greater proportion of respondents in poverty at all levels for minority groups than for white respondents with a similar relationship for females compared to males.

The Bell Curve, written by Murray and Herrnstein, is one of the most controversial books of the last few decades, exploring the role human intelligence plays in predicting a variety of social factors. I examine one of their more notorious conclusions that intelligence, as measured by an IQ test, is a stronger predictor for future poverty than Family's Socioeco­nomic Status. sing the National Longitudinal Survey of Youth (1979), we run regressions examining the relationship between Family SES, IQ test scores, and Age against probability of being in Poverty. Instead of using Bell Curve's method of dropping data that contained incomplete observations, we use an improved method that imputes missing data. i[y results show that IQ does indeed have a greater effect than parental SES on predicting Poverty if the individual is of less than average SES and IQ.